The impact of implantation depth of the Lotus™ valve on mechanical stress in close proximity to the bundle of His

Computational evaluation of interactive dynamics for a full transcatheter aortic valve device in a patient-specific aortic root

Transcatheter aortic valve implantation (TAVI) has become a key treatment for severe aortic stenosis, especially for patients unsuitable for surgery. Since its introduction in 2002, TAVI has advanced significantly due to improvements in imaging, operator skills, and device engineering. Despite these innovations, challenges in device sizing and positioning remain, complicating outcome predictions. Computational modelling is a powerful tool to aid TAVI device design and to understand its interactive behaviour with the aortic root during the deployment. Previous studies often simplified tissue properties, neglected patient-specific geometries or omitted crucial elements such as leaflets and fabric. This paper presents a numerical framework capable of simulating the whole crimping and deployment process of a full TAVI device in a patient-specific aortic root including the native leaflets and calcifications. We conduct a comprehensive investigation into the mechanical behaviour of the TAVI and its interactions with patient-specific aortic root through dynamic finite element analysis during the deployment process, with validation against experimental results. Additionally, we examined the influence of applied pressure during balloon inflation on the interactive dynamics of the entire model. The study concludes that selecting optimal balloon pressures is crucial for enhancing TAVI device performance and reducing complications. Numerical simulations demonstrate that appropriate balloon pressure ensures sufficient flow area and effective contact pressure between the TAVI and the aortic root, while minimising deformation and the risk of paravalvular leak.

Finite Element Analysis of Evolut Transcatheter Heart Valves: Effects of Aortic Geometries and Valve Sizes on Post-TAVI Wall Stresses and Deformations

Background/Objectives: For transcatheter aortic valve implantation (TAVI) therapy, a catheter-guided crimped valve is deployed into the aortic root. Valve types such as Edwards balloon-expandable valves and Medtronic self-expandable valves come in different sizes and are chosen based on patient-specific aortic anatomy, including aortic root diameter measurement. Complications may arise due to variations in anatomical characteristics and the implantation procedure, making pre-implantation assessment important for predicting complications. Methods: Computational modeling, particularly finite element analysis (FEA), has become popular for assessing wall stresses and deformations in TAVI. In this study, a finite element model including the aorta, native leaflets, and TAVI device was used to simulate procedures and assess patient-specific wall stresses and deformations. Results: Using the Medtronic Evolut R valve, we simulated TAVI for 14 patients to analyze the effects of geometrical variations on structural stresses. Virtual TAVIs with different valve sizes were also simulated to study the influence of TAV size on stresses. Our results show that variations in aortic wall geometries and TAV sizes significantly influence wall stresses and deformations. Conclusions: Our study is one of the first comprehensive FEA investigations of aortic geometrical variations and valve sizes on post-TAVI stresses, demonstrating the non-linear relationship between aortic dimensions, TAV sizes, and wall stresses.

Material modeling and recent findings in transcatheter aortic valve implantation simulations

BACKGROUND AND OBJECTIVE

Transcatheter aortic valve implantation (TAVI) has significantly transformed the management of aortic valve (AV) diseases, presenting a minimally invasive option compared to traditional surgical valve replacement. Computational simulations of TAVI become more popular and offer a detailed investigation by employing patient-specific models. On the other hand, employing accurate material modeling procedures and applying basic modeling steps are crucial to determining reliable numerical results. Therefore, this review aims to outline the basic modeling approaches for TAVI, focusing on material modeling and geometry extraction, as well as summarizing the important findings from recent computational studies to guide future research in the field.

METHODS

This paper explains the basic steps and important points in setting up and running TAVI simulations. The material properties of the leaflets, valves, stents, and tissues utilized in TAVI simulations are provided, along with a comprehensive explanation of the geometric extraction methods employed. The differences between the finite element analysis, computational fluid dynamics, and fluid-structure interaction approaches are pointed out and the important aspects of TAVI modeling are described by elucidating the recent computational studies.

RESULTS

The results of the recent findings on TAVI simulations are summarized to demonstrate its powerful potential. It is observed that the material properties of aortic tissues and components of implanted valves should be modeled realistically to determine accurate results. For patient-specific AV geometries, incorporating calcific deposits on the leaflets is essential for ensuring the accuracy of computational findings. The results of numerical TAVI simulations indicate the significance of the selection of optimal valves and precise deployment within the appropriate anatomical position. These factors collectively contribute to the effective functionality of the implanted valve.

CONCLUSIONS

Recent studies in the literature have revealed the critical importance of patient-specific modeling, the selection of accurate material models, and bio-prosthetic valve diameters. Additionally, these studies emphasize the necessity of precise positioning of bio-prosthetic valves to achieve optimal performance in TAVI, characterized by an increased effective orifice area and minimal paravalvular leakage.

Computational Investigation of Vessel Injury Due to Catheter Tracking During Transcatheter Aortic Valve Replacement

Catheter reaction forces during transcatheter valve replacement (TAVR) may result in injury to the vessel or plaque rupture, triggering distal embolization or thrombosis. In vitro test methods represent the arterial wall using synthetic proxies to determine catheter reaction forces during tracking, but whether they can account for reaction forces within the compliant aortic wall tissue in vivo is unknown. Moreover, the role of plaque inclusions is not well understood. Computational approaches have predicted the impact of TAVR positioning, migration, and leaflet distortion, but have not yet been applied to investigate aortic wall reaction forces and stresses during catheter tracking. In this study, we investigate the role that catheter design and aorta and plaque mechanical properties have on the risk of plaque rupture during TAVR catheter delivery. We report that, for trackability testing, a rigid test model provides a reasonable estimation of the peak reaction forces experienced during catheter tracking within compliant vessels. We investigated the risk of rupture of both the aortic tissue and calcified plaques. We report that there was no risk of diseased aortic tissue rupture based on an accepted aortic tissue stress threshold (4.2 MPa). However, we report that both the aortic and plaque tissue exceed a rupture stress threshold (300 kPa) with and without the presence of stiff and soft plaque inclusions. We also highlight the potential risks associated with shorter catheter tips during catheter tracking and demonstrate that increasing the contact surface will reduce peak contact pressures experienced in the tissue.

Latest Developments in Adapting Deep Learning for Assessing TAVR Procedures and Outcomes

Aortic valve defects are among the most prevalent clinical conditions. A severely damaged or non-functioning aortic valve is commonly replaced with a bioprosthetic heart valve (BHV) via the transcatheter aortic valve replacement (TAVR) procedure. Accurate pre-operative planning is crucial for a successful TAVR outcome. Assessment of computational fluid dynamics (CFD), finite element analysis (FEA), and fluid-solid interaction (FSI) analysis offer a solution that has been increasingly utilized to evaluate BHV mechanics and dynamics. However, the high computational costs and the complex operation of computational modeling hinder its application. Recent advancements in the deep learning (DL) domain can offer a real-time surrogate that can render hemodynamic parameters in a few seconds, thus guiding clinicians to select the optimal treatment option. Herein, we provide a comprehensive review of classical computational modeling approaches, medical imaging, and DL approaches for planning and outcome assessment of TAVR. Particularly, we focus on DL approaches in previous studies, highlighting the utilized datasets, deployed DL models, and achieved results. We emphasize the critical challenges and recommend several future directions for innovative researchers to tackle. Finally, an end-to-end smart DL framework is outlined for real-time assessment and recommendation of the best BHV design for TAVR. Ultimately, deploying such a framework in future studies will support clinicians in minimizing risks during TAVR therapy planning and will help in improving patient care.

A review of numerical simulation in transcatheter aortic valve replacement decision optimization

BACKGROUND

Recent trials indicated a further expansion of clinical indication of transcatheter aortic valve replacement to younger and low-risk patients. Factors related to longer-term complications are becoming more important for use in these patients. Accumulating evidence indicates that numerical simulation plays a significant role in improving the outcome of transcatheter aortic valve replacement. Understanding mechanical features' magnitude, pattern, and duration is a topic of ongoing relevance.

METHODS

We searched the PubMed database using keywords such as "transcatheter aortic valve replacement" and "numerical simulation" and reviewed and summarized relevant literature.

FINDINGS

This review integrated recently published evidence into three subtopics: 1) prediction of transcatheter aortic valve replacement outcomes through numerical simulation, 2) implications for surgeons, and 3) trends in transcatheter aortic valve replacement numerical simulation.

INTERPRETATIONS

Our study offers a comprehensive overview of the utilization of numerical simulation in the context of transcatheter aortic valve replacement, and highlights the advantages, potential challenges from a clinical standpoint. The convergence of medicine and engineering plays a pivotal role in enhancing the outcomes of transcatheter aortic valve replacement. Numerical simulation has provided evidence of potential utility for tailored treatments.

Impact of nickel-titanium super-elastic material properties on the mechanical performance of self-expandable transcatheter aortic valves

Self-expandable transcatheter aortic valves (TAVs) elastically resume their initial shape when implanted without the need for balloon inflation by virtue of the nickel-titanium (NiTi) frame super-elastic properties. Experimental findings suggest that NiTi mechanical properties can vary markedly because of a strong dependence on the chemical composition and processing operations. In this context, this study presents a computational framework to investigate the impact of the NiTi super-elastic material properties on the TAV mechanical performance. Finite element (FE) analyses of TAV implantation were performed considering two different TAV frames and three idealized aortic root anatomies, evaluating the device mechanical response in terms of pullout force magnitude exerted by the TAV frame and peak maximum principal stress within the aortic root. The widely adopted NiTi constitute model by Auricchio and Taylor (1997) was used. A multi-parametric sensitivity analysis and a multi-objective optimization of the TAV mechanical performance were conducted in relation to the parameters of the NiTi constitutive model. The results highlighted that: five NiTi material model parameters (E_A, σ_tL^S, σ_tU^S, σ_tU^E and σ_cL^S) are significantly correlated with the FE outputs; the TAV frame geometry and aortic root anatomy have a marginal effect on the level of influence of each NiTi material parameter; NiTi alloy candidates with pareto-optimal characteristics in terms of TAV mechanical performance can be successfully identified. In conclusion, the proposed computational framework supports the TAV design phase, providing information on the relationship between the super-elastic behavior of the supplied NiTi alloys and the device mechanical response.

Inverse material parameter estimation of patient-specific finite element models at the carotid bifurcation: The impact of excluding the zero-pressure configuration and residual stress

The carotid bifurcation experiences a complex loading environment due to its anatomical structure. Previous in-vivo material parameter estimation methods often use simplified model geometries, isotropic hyperelastic constitutive equations or neglect key aspects of the vessel, such as the zero-pressure configuration or residual stress, all of which have independently been shown to alter the stress environment of the vessel wall. Characterizing the location of high stress in the vessel wall has often been proposed as a potential indicator of structural weakness. However, excluding the afore-mentioned zero-pressure configuration, residual stress and patient-specific material parameters can lead to an incorrect estimation of the true stress values observed, meaning that stress alone as a risk indicator of rupture is insufficient. In this study, we investigate how the estimated material parameters and overall stress distributions in geometries of carotid bifurcations, extracted from in-vivo MR images, alter with the inclusion of the zero-pressure configuration and residual stress. This approach consists of the following steps: (1) geometry segmentation and hexahedral meshing from in-vivo magnetic resonance images (MRI) at two known phases; (2) computation of the zero-pressure configuration and the associated residual stresses; (3) minimization of an objective function built on the difference between the stress states of an "almost true" stress field at two known phases and a "deformed" stress field by altering the input material parameters to determine patient-specific material properties; and (4) comparison of the stress distributions throughout these carotid bifurcations for all cases with estimated material parameters. This numerical approach provides insights into the need for estimation of both the zero-pressure configuration and residual stress for accurate material property estimation and stress analysis for the carotid bifurcation, establishing the reliability of stress as a rupture risk metric.

Self-expandable stent for thrombus removal modeling: Solid or beam finite elements?

BACKGROUND

The performance of self-expandable stents is being increasingly studied by means of finite-element analysis. As for peripheral stents, transcatheter valves and stent-grafts, there are numerous computational studies for setting up a proper model, this information is missing for stent-retrievers used in the procedure of thrombus removal in cerebral arteries. It is well known that the selection of the appropriate finite-element dimensions (topology) and formulations (typology) is a fundamental step to set up accurate and reliable computational simulations. In this context, a thorough verification analysis is here proposed, aimed at investigating how the different element typologies and topologies - available to model a stent-retriever - affect simulation results.

METHOD

Hexahedral and beam element formulations were analyzed first individually by virtually replicating a crimping test on the device, and then by replicating the thrombectomy procedure aiming at removing a thrombus from a cerebral vessel. In particular, three discretization refinements for each element type and different element formulations including both full and reduced integration were investigated and compared in terms of the resultant radial force of the stent and the stress field generated in the thrombus.

RESULTS

The sensitivity analysis on the element formulation performed with the crimping simulations allowed the identification of the optimal setting for each element family. Both setting lead to similar results in terms of stent performance in the virtual thrombectomy and should be used in future studies simulating the mechanical thrombectomy with stent-retrievers.

CONCLUSIONS

The carried out virtual thrombectomy procedures confirmed that the beam element formulation results were sufficiently accurate to model the radial force and the performance of the stent-retriever during the procedure. For different self-expandable stents, hexahedral formulation could be essential in stress analysis.

Biomechanics of Transcatheter Aortic Valve Implant

Transcatheter aortic valve implantation (TAVI) has grown exponentially within the cardiology and cardiac surgical spheres. It has now become a routine approach for treating aortic stenosis. Several concerns have been raised about TAVI in comparison to conventional surgical aortic valve replacement (SAVR). The primary concerns regard the longevity of the valves. Several factors have been identified which may predict poor outcomes following TAVI. To this end, the lesser-used finite element analysis (FEA) was used to quantify the properties of calcifications which affect TAVI valves. This method can also be used in conjunction with other integrated software to ascertain the functionality of these valves. Other imaging modalities such as multi-detector row computed tomography (MDCT) are now widely available, which can accurately size aortic valve annuli. This may help reduce the incidence of paravalvular leaks and regurgitation which may necessitate further intervention. Structural valve degeneration (SVD) remains a key factor, with varying results from current studies. The true incidence of SVD in TAVI compared to SAVR remains unclear due to the lack of long-term data. It is now widely accepted that both are part of the armamentarium and are not mutually exclusive. Decision making in terms of appropriate interventions should be undertaken via shared decision making involving heart teams.

On the Modeling of Transcatheter Therapies for the Aortic and Mitral Valves: A Review

Transcatheter aortic valve replacement (TAVR) has become a milestone for the management of aortic stenosis in a growing number of patients who are unfavorable candidates for surgery. With the new generation of transcatheter heart valves (THV), the feasibility of transcatheter mitral valve replacement (TMVR) for degenerated mitral bioprostheses and failed annuloplasty rings has been demonstrated. In this setting, computational simulations are modernizing the preoperative planning of transcatheter heart valve interventions by predicting the outcome of the bioprosthesis interaction with the human host in a patient-specific fashion. However, computational modeling needs to carry out increasingly challenging levels including the verification and validation to obtain accurate and realistic predictions. This review aims to provide an overall assessment of the recent advances in computational modeling for TAVR and TMVR as well as gaps in the knowledge limiting model credibility and reliability.

Systematic Approach to High Implantation of SAPIEN-3 Valve Achieves a Lower Rate of Conduction Abnormalities Including Pacemaker Implantation

BACKGROUND

The conventional method of implanting balloon-expandable SAPIEN-3 (S3) valve results in a final 70:30 or 80:20 ratio of the valve in the aorta:left ventricular outflow tract with published rates of permanent pacemaker around 10%. We sought to evaluate whether higher implantation of S3 reduces conduction abnormalities including the need for permanent pacemaker.

METHODS

We included consecutive patients who underwent transfemoral transcatheter aortic valve replacement using S3 between April 2015 and December 2018 and compared outcomes with typical valve deployment strategy to our more contemporary high deployment technique (HDT). We excluded patients with nontransfemoral access or valve-in-valve.

RESULTS

Among 1028 patients, HDT was performed in 406 patients (39.5%). Mean implantation depth under the noncoronary cusp was significantly smaller with HDT compared with conventional technique (1.5±1.6 versus 3.2±1.9 mm; P<0.001). Successful implantation was achieved in 100% of the patients in both groups with no cases of conversion to open heart surgery, second valve implantation within the first transcatheter aortic valve replacement, or coronary occlusion during transcatheter aortic valve replacement. One patient (0.2%) had valve embolization with HDT (P=0.216). Thirty-day permanent pacemaker rates were lower with HDT (5.5% versus 13.1%; P<0.001), as were rates of complete heart block (3.5% versus 11.2%; P<0.001) and new-onset left bundle branch block (5.3% versus 12.2%; P<0.001). There were no differences in mild (16.5% versus 15.9%; P=0.804), or moderate-to-severe aortic regurgitation (1% versus 2.7%; P=0.081) at 1 year. HDT was associated with slightly higher 1-year mean gradients (13.1±6.2 versus 11.8±4.9 mm Hg; P=0.042) and peak gradients (25±11.9 versus 22.5±9 mm Hg; P=0.026). However, Doppler velocity index was similar (0.47±0.15 versus 0.48±0.13; P=0.772).

CONCLUSIONS

Our novel technique for balloon-expandable S3 valve positioning consistently achieves higher implantation resulting in substantial reduction in conduction abnormalities and permanent pacemaker requirement after transcatheter aortic valve replacement without compromising procedural safety or valve hemodynamics. Operators should consider this as an important technique to improve patient outcomes.

In silico approaches for transcatheter aortic valve replacement inspection

Introduction: Increasing applications of transcatheter aortic valve replacement (TAVR) to treat high- or medium-risk patients with aortic diseases have been proposed in recent years. Despite its increasing use, many influential factors are still to be understood. Furthermore, innovative applications of TAVR such as in bicuspid aortic valves or in low-risk patients are emerging in clinical use. Numerical analyses are increasingly used to reproduce clinical treatments. The future trends in this area are foreseen for in silico trials and personalized medicine. Areas covered: This review paper analyzes the recent years (Jan 2018 - Aug 2020) of in silico studies simulating the behavior of transcatheter aortic valves with emphasis on the addressed clinical question and the used modeling strategies. The manuscripts are firstly classified based on their clinical hypothesis. A second classification is based on the adopted modeling approach in terms of patient domain, device modeling, and inclusion or exclusion of the fluid domain. Expert opinion: The TAVR can be virtually performed in numerous vessel geometries and with different devices. This versatility allows a rapid evaluation of the feasibility of different implantation approaches for specific patients, and patient populations, resulting in faster and safer introduction or optimization of new treatments or devices.

The Impact of Size and Position of a Mechanical Expandable Transcatheter Aortic Valve: Novel Insights Through Computational Modelling and Simulation

Transcatheter aortic valve implantation has become an established procedure to treat severe aortic stenosis. Correct device sizing/positioning is crucial for optimal outcome. Lotus valve sizing is based upon multiple aortic root dimensions. Hence, it often occurs that two valve sizes can be selected. In this study, patient-specific computer simulation is adopted to evaluate the influence of Lotus size/position on paravalvular aortic regurgitation (AR) and conduction abnormalities, in patients with equivocal aortic root dimensions. First, simulation was performed in 62 patients to validate the model in terms of predicted AR and conduction abnormalities using postoperative echocardiographic, angiographic and ECG-based data. Then, two Lotus sizes were simulated at two positions in patients with equivocal aortic root dimensions. Large valve size and deep position were associated with higher contact pressure, while only large size, not position, significantly reduced the predicted AR. Despite general trends, simulations revealed that optimal device size/position is patient-specific.

Patient-specific simulation of transcatheter aortic valve replacement: impact of deployment options on paravalvular leakage

Transcatheter aortic valve replacement (TAVR) has emerged as an effective alternative to conventional surgical valve replacement in high-risk patients afflicted by severe aortic stenosis. Despite newer-generation devices enhancements, post-procedural complications such as paravalvular leakage (PVL) and related thromboembolic events have been hindering TAVR expansion into lower-risk patients. Computational methods can be used to build and simulate patient-specific deployment of transcatheter aortic valves (TAVs) and help predict the occurrence and degree of PVL. In this study finite element analysis and computational fluid dynamics were used to investigate the influence of procedural parameters on post-deployment hemodynamics on three retrospective clinical cases affected by PVL. Specifically, TAV implantation depth and balloon inflation volume effects on stent anchorage, degree of paravalvular regurgitation and thrombogenic potential were analyzed for cases in which Edwards SAPIEN and Medtronic CoreValve were employed. CFD results were in good agreement with corresponding echocardiography data measured in patients in terms of the PVL jets locations and overall PVL degree. Furthermore, parametric analyses demonstrated that positioning and balloon over-expansion may have a direct impact on the post-deployment TAVR performance, achieving as high as 47% in PVL volume reduction. While the model predicted very well clinical data, further validation on a larger cohort of patients is needed to verify the level of the model's predictions in various patient-specific conditions. This study demonstrated that rigorous and realistic patient-specific numerical models could potentially serve as a valuable tool to assist physicians in pre-operative TAVR planning and TAV selection to ultimately reduce the risk of clinical complications.